The addition of Amazon Translate, Amazon Transcribe, and Amazon Comprehend to the list of HIPAA eligible services will allow customers to leverage these AWS ML services to better streamline customer support and improve patient engagement. Customers can use these three services to leverage the following ML capabilities:

Amazon Translate: A neural machine translation service that delivers fast, high-quality, and affordable language translation. This service can be employed to easily translate large volumes of text efficiently and enable patients to chat with their healthcare provider in their preferred language.

Amazon Comprehend: A natural language processing (NLP) service that can find insights and relationships in unstructured text. It can analyze sentiment (e.g., negative, positive, and neutral), and extract key phrases from patient interactions to better understand and improve engagement.

Many healthcare customers are exploring new ways use the power of ML to advance their current workloads and transform how they provide care to patients, all while meeting the requirements of HIPAA.

Zocdoc, a company that provides medical care search for consumers, uses Amazon SageMaker, a platform that enables developers and data scientists to quickly and easily build, train, and deploy ML models, to expedite the amount of time it takes to match patients and doctors.

“At Zocdoc, our focus has been making it easier for patients to find the right doctor and book an appointment at the most convenient time and location. You can imagine the ML use cases. There is a lot of excitement among Zocdoc engineers around how easy it is to quickly build and deploy a model using Amazon SageMaker. As a matter of fact, one of our mobile engineers was able to train and deploy a doctor specialty recommendation model from scratch in less than a day during a recent Zocdoc Hackathon, which we ended up rolling out to production. Previously, our data science team had to contribute to the development of any model work, which slowed down product teams given that the data science team is a shared resource. With Amazon SageMaker, we could get this from concept to a quick production test much faster, due to the ease of streamlined end-to-end build/deploy/test capabilities of Amazon SageMaker. HIPAA eligibility is a welcome improvement and will allow us to expand its use to improve healthcare experience for our patients.”

Aculab has been providing deployment-proven telecom products to the global communication market for nearly 40 years. They are leveraging Amazon Polly, a service that turns text into lifelike speech using deep-learning, to provide telecom solutions for their major healthcare customers.

“One of the key decision points that led Aculab to choose Amazon Polly for our Text-to-Speech (TTS) on the Aculab Cloud platform was the HIPAA support. We have major customers using our system for services such as medical appointment reminders, and we needed a TTS solution that we could use with HIPAA workloads to complement the rest of our HIPAA-compliant architecture. Amazon Polly was able to provide not only a world-class TTS service, but one that could safely handle protected health information,” said David Samuel, CEO of Aculab.

For additional information on Amazon ML services and how healthcare and life sciences companies can run sensitive workloads on AWS refer, to the following materials: